Artificial intelligence in the prediction of environmental and soil temperature in Ecuador

Authors

DOI:

https://doi.org/10.31637/epsir-2025-550

Keywords:

Time series, soil temperature, ambient temperature, artificial intelligence, forecasts, supervised algorithms, Ecuador, ARIMA

Abstract

Introduction: The main objective of the study was to analyze the probability and prediction for environmental and soil temperature in the coastal area of Manabí in Ecuador. Methodology: The methodology makes use of Box Jenkins ARIMA time series and comparison of means. The data was measured at 07:00 am, 12:00 pm and 18:00 pm, starting in January 2015 until December 2020. The data was analyzed and processed with the help of artificial intelligence incorporated into the RStudio software. Results: The results show that soil temperature is correlated with environmental temperature. Discussions: Goodness-of-fit tests for the coefficients and assumptions validated the observed and expected ARIMA model. Furthermore, the AIC and BIC criteria were used to choose the best predictive model. Conclusions: In conclusion, artificial intelligence identified that the prediction of ambient and soil temperatures are adequately simulated through an ARIMA(0,1,1)(0,1,1)[12] model, with trend and seasonality components, By affirming a non-stationary time series model, it is determined that temperature has a small variability for each period of time, but increasing, and in the future this climatic factor will probably become a determinant of global warming.

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Author Biographies

Ángel Ramón Sabando-García, Pontificia Universidad Católica del Ecuador- Sede Santo Domingo (PUCESD)

Master in Statistics; Educational Management and Agricultural Engineering. He works as a research professor at the Pontificia Universidad Católica del Ecuador - Santo Domingo Campus (PUCESD) in Ecuador and is a member of the Planning, Innovation and Financial Modeling Applied Research Group. During his career as a researcher he has published articles in the area of ​​mathematics and statistics, financial modeling, management, agricultural and finance ethics in national and international journals.

Mikel Ugando Peñate, Pontificia Universidad Católica del Ecuador- Sede Santo Domingo (PUCESD)

Doctor in Economics from the Santiago de Compostela University, Spain and Master in Accounting and Finance. He works as a research professor at the Pontificia Universidad Católica del Ecuador - Santo Domingo Campus (PUCESD) in Ecuador and coordinates the Planning, Innovation and Financial Modeling Applied Research Group. He currently coordinates national projects regarding ethical finance and Christian values, as well as the impact of climate change on agricultural production.

Reinaldo Armas Herrera, Universidad Técnica Particular de Loja

Ph.D. in Economics from the University of Las Palmas de Gran Canarias (ULPG), Spain. Master in Finance and Economist from the ULPGC. He is currently a research professor at the Department of Business Sciences, Universidad Técnica Particular de Loja (UTPL), Loja, Ecuador. In his role as a researcher he has specialized in the areas of finance, intellectual capital, university education and ethical finance, publishing articles in national and international journals of great impact.

Angel Alexander Higuerey Gómez, Universidad Técnica Particular de Loja

Doctor in Economics from the University of Las Palmas de Gran Canarias, Spain. Master and Specialist in Tax Law from the Santa María University, Venezuela. Graduate in Administration from the Universidad de Oriente, Venezuela. He currently works as a research professor at UTPL, Ecuador. Recognized researcher belonging to the Experimental Institute of Humanistic, Economic and Social Research (IEXIHES) of the University of Los Andes, Venezuela and the GESCONT research group of the UTPL.

Néstor Leopoldo Tarazona Meza, Escuela Superior Politécnica Agropecuaria de Manabí Manuel Félix López

Professor at the Manabí Agricultural Polytechnic Higher School, in the agricultural engineering degree, meteorology subject. Master in Agricultural Engineering.

Pierina D'Elia Di Michele, Universidad Técnica Particular de Loja

PhD in Education from the Rafael María Baralt University, Venezuela, Graduate in Comprehensive Education, Master in Educational Sciences and Master in Robinsonian Education from UNESR, Venezuela. She is currently a research professor in the Department of Philosophy, Arts and Humanities of the UTPL, Ecuador. She is the promoter of the Research Line: ACPTS-UNESR and member of the EDUFAM-UTPL research group contributing to the Christian Values ​​line.

Elvia Rosalía Inga Llanez, Universidad Técnica Particular de Loja

Master in Accounting and Auditing from the University of Santiago de Chile, has a Diploma in Management Auditing from the University of Santiago de Chile, and is a Commercial Engineer and Graduate in Administration from the Catholic University of Cuenca. He is currently a research professor at the Department of Business Sciences at UTPL and a member of the GESCONT research group.

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2024-11-25

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Sabando-García, Ángel R., Ugando Peñate, M., Armas Herrera, R., Higuerey Gómez, A. A., Tarazona Meza, N. L., D'Elia Di Michele, P., & Inga Llanez, E. R. (2024). Artificial intelligence in the prediction of environmental and soil temperature in Ecuador. European Public & Social Innovation Review, 10, 1–17. https://doi.org/10.31637/epsir-2025-550

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Vol. 10 (2025)

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Copyright (c) 2024 Ángel Ramón Sabando-García, Mikel Ugando Peñate; Reinaldo Armas Herrera (Autor de Correspondencia); Angel Alexander Higuerey Gómez, Néstor Leopoldo Tarazona Meza, Pierina D'Elia Di Michele, Elvia Rosalía Inga Llanez

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